Writing boards such as whiteboards and blackboards are frequently used in many different settings (e.g., academic, corporate, non-profit, residential, etc.). Various content including text, drawings, tables, charts, and graphs may be drawn or placed on the writing boards for lectures, training, brainstorming sessions, etc.
In order to electronically record these ideas, a photograph of the writing board may be taken. Further, image processing such as optical character recognition (OCR), stroke recognition, and reconstruction may be executed to extract the contents of the writing board from the image.
To recognize the content of a table handwritten on a writing board, the image processor or image processing software must locate the pixels that contribute to the “intent” of the table line along with various attributes of the table geometry, such as stroke width and line color. Once the cells of the table are identified, the content included in the cells (e.g., text) can be sent to a recognition module (e.g., OCR module).
However, as shown in FIG. 27, handwritten table lines may have irregularities that arise from, e.g., a worn pen tip, irregular ink distribution, or low ink. These irregularities often appear as smudged, broken, or faded segments, which can be captured in the mask as shown in FIG. 28. Nonetheless, it is desirable to be able to identify such broken segments as a single stroke with a pen for identifying the table line, which enables the content of the table cell to be recognized precisely.